title: Data mining methods in Omics-based biomarker discovery.
abstract: The advent of Omics technologies as genomics and proteomics has brought the hope of discovering novel biomarkers that can be used to diagnose, predict, and monitor the progress of disease. The importance of data mining to identify biological markers for the diagnostic classification and prognostic assessment in the context of microarray and proteomic data has been increasingly recognized. We present an overview of general data mining methods and their applications to biomarker discovery with particular focus on genomics and proteomics data. Two case studies are exemplarily presented, and relevant data mining terminology and techniques are explained.
authors.affiliation: Indiana University School of Informatics, Indianapolis, IN, USA. fanzhang@iupui.edu
authors.forename: Fan
authors.initials: F
authors.lastname: Zhang
authors.forename: Jake Y
authors.initials: JY
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D015415:Biomarkers / Q000378:metabolism; D002853:Chromatography, Liquid; D015179:Colorectal Neoplasms / Q000235:genetics / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D003626:Data Display; D057225:Data Mining / Q000379:methods*; D003663:Decision Trees; D006801:Humans; D016571:Neural Networks, Computer; D025941:Protein Interaction Mapping; D040901:Proteomics; D053719:Tandem Mass Spectrometry
chemical_list: D015415:Biomarkers